The invention relates to fluorescence imaging, and in particular to obtaining and processing fluorescence images, e.g. fluorescence microscopy images.
Fluorescence microscopy is a valuable research and diagnostic tool. One particular type of fluorescence microscopy is the so-called FISH (fluorescence in-situ hybridization) technique. The FISH technique is a well known technique used to detect and localize the presence or absence of specific DNA sequences on chromosomes (which may be referred to as “targets”). The technique relies on the use of fluorescent marker probes designed to bind to target DNA sequences. A specimen to be examined for the target sequence is exposed to the probe material so that molecules comprising the probe bind to target DNA in the specimen (if any). The specimen, which is typically a sample on a slide, is then viewed with a fluorescence microscope to identify regions of the sample which fluoresce due to the presence of the bound fluorescent probe. Fluorescent regions in a fluorescence image correspond with regions containing the target DNA. FISH techniques can also be used to detect and localize specific mRNAs within tissue samples, e.g. to help define spatial-temporal patterns of gene expression within cells and tissues.
Fluorescence microscopy is often practiced as a digital microscopy technique. That it to say, a fluorescence microscope will be used to record a digital image of a sample. The image may then be stored and later retrieved for analysis, e.g., by viewing on a general purpose computer running appropriate software, or on a dedicated monitor associated with the fluorescence microscope itself. The general principles of digital fluorescence microscopy and the obtaining of digital fluorescent microscopy images are well understood and are not describe further here.
Once a digital fluorescence microscopy image has been obtained, it will be analyzed. This may involve a user viewing the image and making a clinical assessment, e.g. to determine if the image displays a pattern of fluorescence that indicates a particular condition, e.g. based on the identified presence/distribution of the target DNA to which the fluorescent molecule (fluorophore) has bound. Alternatively, or in addition, the digital fluorescence microscopy image may be analyzed using digital image processing techniques. For example, the image may be automatically processed to count the number of spots of fluorescence (bright spots) in the image using numerical processing techniques. Automated image processing techniques can provide a higher throughput of analyzed images that would typically be the case if each image is manually inspected/analyzed.
A drawback of digital fluorescence microscopy is that fluorescence images are often unable to represent all of the available information about the distribution of a fluorophore probe in the sample, e.g. a microscope's optics will often not have a large enough depth of field for all spots (fluorescent structures) to be in focus in a single image. Furthermore, it is often the case that the level of fluorescence associated with the presence of the target DNA varies across an image, even for a uniform distribution of target DNA. Images can also be affected by background light and non-specific auto-fluorescence which can reduce the contrast of target DNA marked with the fluorescent probe in the image.
These drawbacks mean that distinguishing and identifying target structures (e.g. fluorophore-labeled DNA in the FISH technique) can be problematic, both for humans and for automatic image processing systems/algorithms. These problems can be exacerbated for specimens containing material from different types of tissue, e.g. lung or prostate, such as may be found in a TMA (tissue micro-array) slide. This is because different tissue-types can absorb the fluorescent probe dyes differently. This means a typical spot-counting task can become difficult because the fluorescence intensity of spots in some tissue types can be very different from the fluorescence intensity of spots in other tissue types because of the different affinities of the two tissue types to the fluorophore probe. For example, spots in one type of tissue might be very bright whilst corresponding spots in another tissue type might be almost invisible. Another factor which can affect staining intensity is specimen thickness. This can lead to variations in fluorophore-labeled spot intensity (and other structures) in fluorescent microscopy images, even for a single tissue type with a uniform distribution of the target of interest.
There is therefore a need for schemes for obtaining and processing fluorescent microscopy images which are less affected by the above-mentioned drawbacks.